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CMakeLists.txt (603, 2018-02-28)
LICENSE (1075, 2018-02-28)
images (0, 2018-02-28)
images\unscented-kf.png (57988, 2018-02-28)
src (0, 2018-02-28)
src\Eigen (0, 2018-02-28)
src\Eigen\Array (304, 2018-02-28)
src\Eigen\CMakeLists.txt (607, 2018-02-28)
src\Eigen\Cholesky (775, 2018-02-28)
src\Eigen\CholmodSupport (1670, 2018-02-28)
src\Eigen\Core (12826, 2018-02-28)
src\Eigen\Dense (122, 2018-02-28)
src\Eigen\Eigen (37, 2018-02-28)
src\Eigen\Eigen2Support (3295, 2018-02-28)
src\Eigen\Eigenvalues (1394, 2018-02-28)
src\Eigen\Geometry (1605, 2018-02-28)
src\Eigen\Householder (580, 2018-02-28)
src\Eigen\IterativeLinearSolvers (1594, 2018-02-28)
src\Eigen\Jacobi (645, 2018-02-28)
src\Eigen\LU (983, 2018-02-28)
src\Eigen\LeastSquares (712, 2018-02-28)
src\Eigen\MetisSupport (697, 2018-02-28)
src\Eigen\OrderingMethods (2189, 2018-02-28)
src\Eigen\PaStiXSupport (1467, 2018-02-28)
src\Eigen\PardisoSupport (864, 2018-02-28)
src\Eigen\QR (926, 2018-02-28)
src\Eigen\QtAlignedMalloc (637, 2018-02-28)
src\Eigen\SPQRSupport (930, 2018-02-28)
src\Eigen\SVD (858, 2018-02-28)
src\Eigen\Sparse (594, 2018-02-28)
src\Eigen\SparseCholesky (1433, 2018-02-28)
src\Eigen\SparseCore (1835, 2018-02-28)
src\Eigen\SparseLU (1776, 2018-02-28)
src\Eigen\SparseQR (991, 2018-02-28)
src\Eigen\StdDeque (749, 2018-02-28)
src\Eigen\StdList (682, 2018-02-28)
src\Eigen\StdVector (755, 2018-02-28)
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# Unscented Kalman Filter Sensor Fusion In this project an Unscented Kalman Filter is used to estimate the state of a moving object of interest with noisy lidar and radar measurements. [//]: # (Image References) [image01]: ./images/unscented-kf.png "Unscented Kalman Filter" ## Requirements This project requires the Udacity Term 2 Simulator which can be downloaded [here](https://github.com/udacity/self-driving-car-sim/releases) It also requires the [uWebSocketIO](https://github.com/uWebSockets/uWebSockets) library. Here are some notes about how to build and install the proper version of the library on an Ubuntu system: sudo apt-get update sudo apt-get install git libuv1-dev libssl-dev gcc g++ cmake make git clone https://github.com/uWebSockets/uWebSockets cd uWebSockets git checkout e94b6e1 mkdir build cd build cmake .. make sudo make install cd ../.. sudo ln -s /usr/lib***/libuWS.so /usr/lib/libuWS.so sudo rm -r uWebSockets ## Other Important Dependencies * cmake >= 3.5 * gcc/g++ >= 5.4 ## Build Instructions Once the install for uWebSocketIO is complete, the main program can be built and run by doing the following from the project top directory. 1. Clone this repository 2. mkdir build 3. cd build 4. cmake .. 5. make ## How to Run ### Start the simulator Start the simulator and select the EKF scenario in the simulator: ./term2_sim_linux/term2_sim.x86_*** ### Run the Unscented Kalman Filter The executable can then be started: ./UnscentedKF Once this is done just press the "Start" button in the simulator and watch the fireworks. ### How it Works The UKF executable is using a simple protocol using uWebSocketIO to communicate with the simulator exchanging JSON-formatted messages. INPUT: values provided by the simulator to the c++ program * ["sensor_measurement"] => the measurement that the simulator observed (either lidar or radar) OUTPUT: values provided by the c++ program to the simulator * ["estimate_x"] <= kalman filter estimated position x * ["estimate_y"] <= kalman filter estimated position y * ["rmse_x"] * ["rmse_y"] * ["rmse_vx"] * ["rmse_vy"] ## Results Here is a screenshot of the simulation results: ![test result][image01]

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